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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72241
Title: 
Statistical model applied to NetFlow for network intrusion detection
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
ISSN: 
  • 0302-9743
  • 1611-3349
Abstract: 
The computers and network services became presence guaranteed in several places. These characteristics resulted in the growth of illicit events and therefore the computers and networks security has become an essential point in any computing environment. Many methodologies were created to identify these events; however, with increasing of users and services on the Internet, many difficulties are found in trying to monitor a large network environment. This paper proposes a methodology for events detection in large-scale networks. The proposal approaches the anomaly detection using the NetFlow protocol, statistical methods and monitoring the environment in a best time for the application. © 2010 Springer-Verlag Berlin Heidelberg.
Issue Date: 
31-Dec-2010
Citation: 
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 6480, n. PART 2, p. 179-191, 2010.
Time Duration: 
179-191
Keywords: 
  • anomaly
  • intrusion detection
  • NetFlow
  • network
  • Security
  • statistical
  • NetFlows
  • Internet protocols
  • Network security
  • Intrusion detection
Source: 
http://dx.doi.org/10.1007/978-3-642-17697-5_9
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/72241
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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